جستجوی استاد راهنمای دانشگاهی

Joann Jasiakمشاهده پروفایل

استاد

• Econometrics
• Time Series Analysis
• Noncausal Processes
• +۵ مورد دیگر

Joann Jasiak is a Professor in the Department of Economics at York University, affiliated with the Faculty of Liberal Arts & Professional Studies. She holds a PhD from the University of Montreal. Her research focuses on econometrics and time series analysis, with recent work emphasizing noncausal processes, stationary martingales, and applications to financial and economic data, including cryptocurrency markets and bubble detection. She has also contributed to cybersecurity analysis in Canadian businesses and epidemiological modeling using stochastic methods. Her research interests span econometric theory, financial econometrics, and the analysis of time series data with noncausal structures. Key areas include developing methodologies for forecasting cryptocurrency returns, modeling common bubbles in asset prices, and optimizing covariance estimation techniques for noncausal processes. Her work integrates advanced statistical tools with real-world applications in finance, economics, and public health. Recent publications (2023–2025) highlight her contributions to topics such as cryptocurrency dynamics, stochastic tree models for asset pricing, and generalized covariance-based inference. Her articles frequently address methodological challenges in econometrics and their practical implications for understanding market behaviors and economic phenomena. Dr. Jasiak’s work has not been explicitly linked to awards or major grants in the provided texts, though her extensive publication record reflects sustained academic engagement. No lab or team affiliations are mentioned in the available data.

• Biomedical Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۴ مورد دیگر

Hoifung Poon is General Manager at Microsoft Health Futures and affiliated faculty at University of Washington Medical School. He leads Real-World Evidence (RWE) research focusing on AI applications for precision health. Poon earned a B.S. with Distinction in Computer Science from Sun Yat-Sen University and a Ph.D. in Computer Science and Engineering from University of Washington. Specializes in biomedical AI research Focuses on structuring unstructured medical data Co-PI for DARPA Big Mechanisms projects Research strength lies in biomedical multimodal learning (text, radiology, pathology, genomics) and causal learning for real-world evidence generation. His team develops methods for LLM self-verification , multi-modal fusion , and biases correction in observational data. Publications show expertise in Nature , Nature Methods , and NEJM AI , covering topics from digital pathology to clinical text analysis. Scientific recognition includes: Best Paper Awards at NAACL, EMNLP, and UAI Winner of ACM Health Best Paper Award Named Technology Champion 2022 by Puget Sound Business Journal

• Constitutional Law
• Comparative Constitutional Law
• Federalism
• +۳ مورد دیگر

Fatih Öztürk serves as Associate Professor in Constitutional Law at Istanbul University's Faculty of Law, where he conducts research on public participation in constitution-making processes and the application of check-and-balances mechanisms within presidential systems. His academic credentials include: L.L.B. from Istanbul University, Turkey L.L.M. from California Western University, USA L.L.M. from Queen's University, Canada (2005) Ph.D. from Istanbul University, Turkey Professor Öztürk's scholarly work centers on Constitutional Law with deep specialization in Comparative Constitutional Systems . His research critically examines Federalism through comparative analysis of American and Canadian models, as demonstrated in his 2021 monograph ABD ve Kanada Federalizmi . He investigates Judicial Activism and the Political Question doctrine in constitutional adjudication, particularly in the fourth edition (2021) of Karşılaştırmalı Anayasa Yargısında Politik Sorun ve Yargısal Aktivizm Doktrini . A significant portion of his scholarship addresses the intersection of law and religion, focusing on Religious Freedom protections under international frameworks like the ECHR and UN systems, alongside analysis of Minority Rights with specific attention to failures in liberal theories of minority protection. His major publications include the 2021 triad: ABD ve Kanada Federalizmi (American and Canadian Federalism), the fourth edition of Karşılaştırmalı Anayasa Yargısında Politik Sorun ve Yargısal Aktivizm Doktrini , and the third edition of Yeni Anayasa İçin Yol Haritası (A Route Map for a New Constitution for Turkey). Additional works encompass the translated volume Hukuk ve Din (Law and Religion, 2019), Essays in Turkish and Comparative Law (2013), Ottoman & Turkish Law (2014), and the Carolina Academic Press-edited volume A Road Map of a New Constitution for Turkey (2014).

Peter Fisherمشاهده پروفایل

استادیار

• Recruitment
• Selection
• Workplace Diversity
• +۳ مورد دیگر

Peter Fisher is an Assistant Professor of Organizational Behavior and Human Resource Management at Ryerson University's Ted Rogers School of Management. His research specializes in bias reduction in hiring, workplace diversity, and evidence-based recruitment practices. He also serves as webmaster for the Canadian Society for Industrial Organizational Psychology. Research Focus Fisher investigates personnel selection methodologies, cross-cultural personality differences, and HR decision-making. Key areas include: Gender and cultural bias mitigation in employment references Personality assessment validity (e.g., forced-choice testing) Technology's role in modern recruitment Publications His 9 most recent articles (2017–2021) emphasize industrial-organizational psychology, with recurring themes of psychometrics, cross-national comparisons, and HR analytics. Work frequently appears in journals like Personality and Individual Differences and the International Journal of Selection and Assessment . Awards & Grants SSHRC Insight Development Grant (2020–2021): $50,574 for tech startup hiring research Lazaridis Seed Grant (2019–2020): $10,000 2017 Best Master’s Thesis Award (HR Research Institute) 2017 Best Student Poster, Second Prize (Canadian Society for I/O Psychology) Teaching & Service He teaches MHR 623: Recruitment and Selection and contributes to academic societies, enhancing industry-academia collaboration in HR practices.

Georgina Maria Tinungkiمشاهده پروفایل

استاد

• Mathematics Education
• Statistics Education
• Applied Statistics
• +۴ مورد دیگر

Professor Georgina Maria Tinungki is a distinguished academic serving as a Full Professor at Hasanuddin University's Department of Statistics within the Faculty of Mathematics and Natural Sciences. She simultaneously holds an Associate Professor position at Makassar Merchant Marine Polytechnic in the Sea and Port Transportation Management department and serves as Head of Department at Hasanuddin University since September 2019. With a career spanning over three decades since her initial lecturer position at Christian University of Indonesia Paulus (1989-1991), Professor Tinungki has established herself as a leading figure in statistics and mathematics education in Indonesia. PhD in Educational Mathematics and Statistics from Indonesia University of Education (2016) PhD in Coastal and Marine Resources from IPB University (2005) MSc in Statistics from IPB University (2000) Dra in Mathematics (equivalent to Master's degree) Professor Tinungki's research spans multiple interconnected domains with particular emphasis on mathematics and statistics education, applied statistics, mathematical modeling, and coastal and marine resource management. Her recent work demonstrates a strong focus on financial applications, particularly examining dividend policy during the COVID-19 pandemic using sophisticated panel data approaches. She has made significant contributions to educational methodology through her research on Team-Assisted Individualization (TAI) cooperative learning models that enhance mathematical problem-solving, communication, and self-proficiency among students. Her methodological expertise includes advanced statistical techniques such as copula methods for risk assessment, geographically weighted regression, and robust statistical approaches for handling outliers and non-normal data. Postgraduate scholarship from Directorate General of Higher Education for 2nd PhD degree study (2011) Postgraduate scholarship from Directorate General of Higher Education for PhD degree study (2001) Postgraduate scholarship from Directorate General of Higher Education for Master degree study (1997) With 77 publications and 585 citations, Professor Tinungki maintains an active research program with recent publications spanning finance, education, and statistical methodology. Her work on dividend policy during the pandemic demonstrates rigorous application of both static and dynamic panel data models. In education research, she continues to refine cooperative learning approaches with particular attention to developing students' self-proficiency alongside technical skills. Her laboratory work focuses on applying statistical methods to real-world problems in finance, education, and resource management, often collaborating with colleagues across multiple institutions. Professor Tinungki leads Georgina Maria Tinungki's Lab, which focuses on interdisciplinary research bridging statistics, education, and practical applications. The lab environment emphasizes methodological rigor while addressing real-world challenges in financial modeling, educational assessment, and resource management. Current projects include analyzing market reactions to corporate policies during crises, developing innovative statistical teaching methods, and applying spatial statistics to socioeconomic issues in Indonesia.

Sean Kauffmanمشاهده پروفایل

استادیار

• Formal Methods
• Real-time Systems
• Software Engineering
• +۴ مورد دیگر

Sean Kauffman is an Assistant Professor in the Department of Electrical and Computer Engineering at Queen's University, Faculty of Engineering and Applied Science. He holds his office in Walter Light Hall, Room 611, and can be reached at sean.k@queensu.ca or by phone at 613-533-6000 ext. 77360. Dr. Kauffman earned his Ph.D. in Electrical and Computer Engineering from the University of Waterloo before completing a two-year postdoctoral position at Aalborg University in Denmark. Notably, he returned to academia after accumulating over a decade of industry experience as a software engineer, with his final industry role being Principal Software Engineer at Oracle. His research expertise spans several critical areas in computer science and software engineering, with a particular focus on safety-critical software systems. His work significantly contributes to the fields of Formal Methods, Runtime Verification, Anomaly Detection, and Explainable AI. Dr. Kauffman has established productive research collaborations with prestigious organizations including NASA's Jet Propulsion Laboratory, the Embedded Systems Institute, QNX, and Pratt and Whitney Canada. Dr. Kauffman's research output demonstrates a consistent focus on event stream analysis, formal verification techniques, and the development of practical tools for system monitoring. His most notable contribution is the nfer language and toolset, which has become influential in the runtime verification community for its ability to abstract event streams into meaningful temporal hierarchies. His publications reveal a progression from theoretical foundations to practical implementations, with applications spanning spacecraft telemetry, autonomous vehicles, and embedded systems. Among his scientific contributions, Dr. Kauffman has received recognition for his work on the complexity analysis of nfer evaluation, developing methods for annotating control-flow graphs for formalized test coverage criteria, and creating frameworks for anomaly detection in embedded systems. His research has been published in top-tier venues including Science of Computer Programming, International Journal on Software Tools for Technology Transfer, and proceedings of major conferences like Runtime Verification and NASA Formal Methods. As an educator, Dr. Kauffman employs active learning techniques, productive failure approaches, and peer instruction to foster student engagement. His industry background informs his teaching approach, providing students with practical insights into real-world software engineering challenges, particularly in safety-critical domains. Dr. Kauffman leads the CritLab research group at Queen's University, which focuses on critical systems research. The lab develops tools and techniques for analyzing and verifying systems where failures could have severe consequences, with applications in aerospace, automotive, and other safety-critical domains. His work on the nfer language has spawned related projects including nvis for visualizing temporal interval hierarchies.